111 lines
4.6 KiB
Python
Executable File
111 lines
4.6 KiB
Python
Executable File
#!/usr/bin/env python
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# -*- coding: UTF-8 no BOM -*-
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import os,sys,math
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import numpy as np
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from optparse import OptionParser
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from PIL import Image
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import damask
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scriptName = os.path.splitext(os.path.basename(__file__))[0]
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scriptID = ' '.join([scriptName,damask.version])
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#--------------------------------------------------------------------------------------------------
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# MAIN
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#--------------------------------------------------------------------------------------------------
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parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [file[s]]', description = """
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Generate geometry description from (multilayer) images.
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Microstructure index is based on gray scale value (1..256).
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""", version = scriptID)
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parser.add_option('--homogenization',
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dest = 'homogenization',
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type = 'int', metavar = 'int',
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help = 'homogenization index [%default]')
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parser.set_defaults(homogenization = 1,
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)
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(options,filenames) = parser.parse_args()
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# --- loop over input files -------------------------------------------------------------------------
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if filenames == []: filenames = [None]
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for name in filenames:
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try:
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table = damask.ASCIItable(name = name,
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outname = os.path.splitext(name)[0]+'.geom' if name else name,
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buffered = False, labeled = False)
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except: continue
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table.croak('\033[1m'+scriptName+'\033[0m'+(': '+name if name else ''))
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# --- read image ------------------------------------------------------------------------------------
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img = Image.open(name).convert(mode = 'L') # open and convert to grayscale 8bit
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slice = 0
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while True:
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try:
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img.seek(slice) # advance to slice
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layer = np.expand_dims(1+np.array(img,dtype = 'uint16'),axis = 0) # read image layer
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microstructure = layer if slice == 0 else np.vstack((microstructure,layer)) # noqa
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slice += 1 # advance to next slice
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except EOFError:
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break
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# http://docs.scipy.org/doc/scipy/reference/ndimage.html
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# http://scipy-lectures.github.io/advanced/image_processing/
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info = {
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'grid': np.array(microstructure.shape,'i')[::-1],
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'size': np.array(microstructure.shape,'d')[::-1],
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'origin': np.zeros(3,'d'),
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'microstructures': len(np.unique(microstructure)),
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'homogenization': options.homogenization,
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}
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# --- report ---------------------------------------------------------------------------------------
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table.croak(['grid a b c: %s'%(' x '.join(map(str,info['grid']))),
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'size x y z: %s'%(' x '.join(map(str,info['size']))),
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'origin x y z: %s'%(' : '.join(map(str,info['origin']))),
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'homogenization: %i'%info['homogenization'],
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'microstructures: %i'%info['microstructures'],
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])
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errors = []
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if np.any(info['grid'] < 1): errors.append('invalid grid a b c.')
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if np.any(info['size'] <= 0.0): errors.append('invalid size x y z.')
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if errors != []:
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table.croak(errors)
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table.close(dismiss = True)
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continue
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# --- write header ---------------------------------------------------------------------------------
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table.info_clear()
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table.info_append([
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scriptID + ' ' + ' '.join(sys.argv[1:]),
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"grid\ta {grid[0]}\tb {grid[1]}\tc {grid[2]}".format(grid=info['grid']),
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"size\tx {size[0]}\ty {size[1]}\tz {size[2]}".format(size=info['size']),
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"origin\tx {origin[0]}\ty {origin[1]}\tz {origin[2]}".format(origin=info['origin']),
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"homogenization\t{homog}".format(homog=info['homogenization']),
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"microstructures\t{microstructures}".format(microstructures=info['microstructures']),
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])
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table.labels_clear()
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table.head_write()
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table.output_flush()
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# --- write microstructure information ------------------------------------------------------------
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formatwidth = int(math.floor(math.log10(microstructure.max())+1))
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table.data = microstructure.reshape((info['grid'][1]*info['grid'][2],info['grid'][0]),order='C')
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table.data_writeArray('%%%ii'%(formatwidth),delimiter = ' ')
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# --- output finalization --------------------------------------------------------------------------
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table.close() # close ASCII table
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